Matplotlib.pyplot.plot_date() function in Python
Matplotlib is a module or package or library in python which is used for data visualization. Pyplot is an interface to a Matplotlib module that provides a MATLAB-like interface.
Matplotlib.pyplot.plot_date ()
This function used to add dates to the plot.
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Syntax:
matplotlib.pyplot.plot_date(x, y, fmt=’o’, tz=None, xdate=True, ydate=False, data=None, **kwargs)
This is the syntax of date function. It contains various parameters or arguments which are explained below.
S.no. | Parameter/Arguments | Description |
1. | x, y | x and y both are the coordinates of the data i.e. x-axis horizontally and y-axis vertically. |
2. | fmt | It is a optional string parameter that contains the corresponding plot details like color, style etc. |
3. | tz | tz stands for timezone used to label dates, default(UTC). |
4. | xdate | xdate parameter contains boolean value. If xdate is true then x-axis is interpreted as date in matplotlib. By default xdate is true. |
5. | ydate | If ydate is true then y-axis is interpreted as date in matplotlib. By default ydate is false. |
6. | data | The data which is going to be used in plot. |
The last parameter **kwargs is the Keyword arguments control the Line2D properties like animation, dash_ joint-style, colors, linewidth, linestyle, marker, etc.
Example 1:
Python3
# importing librariesimport matplotlib.pyplot as pltfrom datetime import datetime # creating array of dates for x axisdates = [ datetime(2020, 6, 30), datetime(2020, 7, 22), datetime(2020, 8, 3), datetime(2020, 9, 14)] # for y axisx = [0, 1, 2, 3] plt.plot_date(dates, x, 'g')plt.xticks(rotation=70)plt.show() |
Output:
Example 2: Creating a plot using dataset.
Python3
# importing librariesimport pandas as pdimport matplotlib.pyplot as pltfrom datetime import datetime # creating a dataframedata = pd.DataFrame({'Date': [datetime(2020, 6, 30), datetime(2020, 7, 22), datetime(2020, 8, 3), datetime(2020, 9, 14)], 'Close': [8800, 2600, 8500, 7400]}) # x-axisprice_date = data['Date'] # y-axisprice_close = data['Close'] plt.plot_date(price_date, price_close, linestyle='--', color='r')plt.title('Market', fontweight="bold")plt.xlabel('Date of Closing')plt.ylabel('Closing Amount') plt.show() |
Output:
Example 3: Changing the format of the date:
Python3
# importing librariesimport pandas as pdimport matplotlib.pyplot as pltfrom datetime import datetime # creating a dataframedata = pd.DataFrame({'Date': [datetime(2020, 6, 30), datetime(2020, 7, 22), datetime(2020, 8, 3), datetime(2020, 9, 14)], 'Close': [8800, 2600, 8500, 7400]}) # x-axisprice_date = data['Date'] # y-axisprice_close = data['Close'] plt.plot_date(price_date, price_close, linestyle='--', color='r')plt.title('Market', fontweight="bold")plt.xlabel('Date of Closing')plt.ylabel('Closing Amount') # Changing the formate of the date using# dateformatter classformat_date = mpl_dates.DateFormatter('%d-%m-%Y') # getting the accurate current axes using gca()plt.gca().xaxis.set_major_formatter(format_date) plt.show() |
Output:
The format of the date changed to dd-mm-yyyy. To know more about dataformatter and gca() click here.
